Field data collection is essential for accurate satellite image interpretation, as it aims to bring into view the ground level reality that satellite images sense from a distance. This in turn, allows to build interpretative models of satellite data that can map with some accuracy to ground level phenomena. Generally, the more field data is collected, the better these models become.  Smart field data collection campaigns attempt to sample a cross-section of the phenomena of interest so that all relevant phenomena are represented.  These campaigns are expensive (labour, tools, logistics to negotiate geographic spread) and thus require careful planning.

With respect to the application of RS in agricultural management, field data collection provides relevant information such as the crops cultivated, agronomic practices adopted by the farmer and data on the growth of crops (e.g., development of plant height, density, and ground cover). Collectively, such information assists analysts to correctly interpret RS images, put labels on features in the image, and eventually support making decisions, whether by farmers, actors in the food industry, or by agricultural policy makers up in the governance pyramid.

This section highlights some of the essential field parameters that are often collected during field campaigns to aid in the analysis of RS data. Specific attention is given to remote sensing applications to agricultural management. Where applicable, equipment that is required to measure these parameters is described and discussed. The section has three subsections:

  1. field level surveys,
  2. measurement equipment and
  3. measurement protocols.